Fragmentation leads to unpredictable and degraded application performance. While these problems have been studied in detail for desktop filesystem workloads, this study examines newer systems such as scalable object stores and multimedia repositories. Such systems use a get/put interface to store objects. In principle, databases and filesystems can support such applications efficiently, allowing system designers to focus on complexity, deployment cost and manageability. Although theoretical work proves that certain storage policies behave optimally for some workloads, these policies often behave poorly in practice. Most storage benchmarks focus on short-term behavior or do not measure fragmentation. We compare SQL Server to NTFS and find that fragmentation dominates performance when object sizes exceed 256KB-1MB. NTFS handles fragmentation better than SQL Server. Although the performance curves will vary with other systems and workloads, we expect the same interactions between fragmentation and free space to apply. It is well-known that fragmentation is related to the percentage free space. We found that the ratio of free space to object size also impacts performance. Surprisingly, in both systems, storing objects of a single size causes fragmentation, and changing the size of write requests affects fragmentation. These problems could be addressed with simple changes to the filesystem and database interfaces. It is our hope that an improved understanding of fragmentation will lead to predictable storage systems that require less maintenance after deployment.